Host Infrastructure Analysis for Pre-Attack Malicious Host Detection
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Solution Overview
Problem
Conventional cybersecurity systems react to cyber-attacks after they occur, failing to detect malicious hosts until after they have initiated an attack, allowing them to be removed and reinserted for further attacks.
Innovation Solution
A cybersecurity system with a host infrastructure analysis system that retrieves and analyzes salient characteristics of network hosts using querying logic, conducts a dual-stage analysis to classify hosts as suspicious or malicious, and generates reports to prevent attacks before they happen.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional cybersecurity systems react to cyber-attacks after they occur, then the system complexity is reduced, but the detection timing is delayed and malicious hosts can be removed and reinserted for further attacks
Solution Approach 1:
The system performs preliminary analysis of host infrastructure characteristics before cyber-attacks occur. By proactively scanning and analyzing network hosts for suspicious characteristics (such as unusual service configurations, unrecognized software, or anomalous network behavior patterns), the system identifies and blocks malicious hosts before they can launch attacks, thereby reducing detection timing loss without requiring overly complex real-time intervention mechanisms
Solution Approach 2:
The cybersecurity system is divided into separate functional modules: a scanning module that collects host infrastructure data, an analysis module that processes characteristics against threat profiles, and a blocking module that executes mitigations. This segmentation allows each component to operate independently with optimized complexity, improving overall detection timing while keeping individual module complexity manageable
2Measurement precision
If the system analyzes all host characteristics in detail, then the measurement precision of malicious host identification is improved, but the processing time and system resources increase
Solution Approach 1:
The system applies different analysis depths to different host characteristics based on their suspiciousness level. Critical characteristics (such as unrecognized services or anomalous port configurations) receive detailed analysis, while less suspicious characteristics receive minimal processing. This local quality approach maintains high identification accuracy for malicious hosts while reducing overall processing time by avoiding uniform deep analysis of all characteristics
Solution Approach 2:
The system pre-establishes threat profiles and characteristic thresholds before actual analysis occurs. By having pre-defined malicious behavior patterns and characteristic weightings ready in advance, the system can rapidly compare new host data against these pre-prepared reference frameworks, achieving precise identification without time-consuming real-time analysis of all possible characteristics
Data Source
AI summary
According to one embodiment, host infrastructure analysis logic that attempts to detect a malicious host operating within a network prior to a cyber-attack being conducted by the malicious host is described. The host infrastructure analysis logic includes querying logic, profile confirmation logic, classification logic and reporting logic. The querying logic retrieves salient characteristics associated with a plurality of hosts operating within the network and determines whether any hosts are suspicious. The profile confirmation logic, if a suspicious host is detected, establishes communications with that suspicious host to retrieve additional context information. The classification logic, based on the retrieved information, determines whether the suspicious host is malicious, prior to and without reliance on information associated with a cyber-attack being conducted by that host. The reporting logic outputs analytic results identifying at least the suspicious host is operating as a malicious host.